​AI and ML workflows are notoriously slow and expensive. Engineers wait days and weeks for models to train. CFOs see AWS bills balloon. Even policymakers warn of compute shortages. But there’s a better way.

​By reengineering long-running workflows with functional Python, organizations can unlock multifold cost savings and speed improvements, without adding more hardware.

​This webinar explores how techniques like persistent memoization and deterministic parallelism, powered by functional programming, can dramatically streamline data-intensive processes. 

​Learn about modern open-source tools that can super-charge your workflows. The webinar will cover the underlying theory and dive into practical, hands-on demos. 

​Speaker

​Vlad Pavlov, hands-on AI engineering leader and open-source enthusiast, with 20+ years at startups to Microsoft & Intel. Vlad led major projects in Martech (1Bln+ consumers), Healthcare, Telecom (600Mln+ consumers). He is an award-winning researcher, author, and speaker.

​Data Phoenix Webinars

​We at Data Phoenix are excited to resume our series of free technical webinars.

​Our first one is coming up on August 27, and for the first time, we’re running two live sessions to cover multiple time zones, so you can join from wherever you are. This session is better suited for participants from the Americas & Europe. If you're joining from Asia or Australia, please register for the other session here.

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